The right data points are the basis of every investment decision

Article originally published in The Intermediary August 2023 – page  74

As I write, Europe is in the grip of another searing heatwave. This is heat that kills. Italy, Spain and Greece are recording temperatures in excess of 45C. Temperatures in California’s Death Valley, hit 53.3C in mid-July according to the US National Weather Service – the highest ever recorded on Earth.

Aside from the fear induced by such visceral evidence of the rapid pace of global warming and the toll it is already taking on human and animal lives, the consequences of climate change are already material. Interspersed between periods of extreme heat in the UK we have seen torrential rain.

Remember that image of the Prime Minister Rishi Sunak standing over a Darlington pothole, promising a “clampdown” on the UK’s crumbling roads ahead of May’s local elections? The same strain is weighing on the UK’s housing stock; investors, whose capital our market and therefore economy relies on, are all too aware that climate risk is increasingly a threat to the value of their investments.

Pricing in risk

As the past 18 months have shown, even the best of us cannot predict the future. Bank of England forecasts relating to inflation and thus its monetary policy have been under the spotlight as such rapid changes in the data at their disposal puts them on the backfoot.

A report published by the Resolution Foundation in July suggested that house prices would fall 25 per cent should interest rates keep rising from their current 5 per cent. Markets are pricing that in already. Rightmove recorded a £5,000 fall in asking prices in the south east between June and July, bringing the average down to £490,386. UK-wide, asking prices fell by more than £900 on the month to an average of £371,907.In the short-term, the data is variable and highly liable to change. For investors providing wholesale funding to UK mortgage lenders, it is yet one more reason to underwrite credit lines with robust capital valuations.

Using AVMs

Mortgage finance is a long-term game, one that throws off steady cashflows and, historically, strong capital growth at maturity. Investors know this, but increasingly the way that capital valuations are weighted is shifting to reflect the changing risk environment. A higher dependence on automated valuation models can give clear, data driven insight into timely capital valuation of the underlying assets in a mortgage book. It can assess the margin of loss a book can safely tolerate on both capital value and income risk.

Relying solely on AVM valuations – even with a degree of triage for outliers needing a more detailed physical evaluation – has its limits. Climate change and its effect on structural soundness over the next quarter of a century is hard for an algorithm to predict statistically – at least on a particular property.

Overall, a consensus risk exposure can be estimated for a large enough book of mortgages ready for securitisation or other refinance models. But investors want more granularity than this now. The risks are too many and too new to trust solely in necessarily backward-looking models, regardless of how predictive they claim to be.

Additional input

I have said it before, but it bears revisiting: RICS is of the view that AVMs can be useful to tease out nuances and aid with statistical analysis that valuers may not ordinarily be able to observe in the course of their usual investigations. That is a positive and adds robustness to the data we have.

On the other hand, the property is not usually inspected when an AVM is used. Instead an average condition is often used, which RICS admits “could well be inaccurate”. Condition and age of a property do not necessarily correlate. Location cannot be simplified by flood plain and local soil absorption.

Additional data points are key and understanding what and how we use them is fundamental to long-term successful investment, funding and lending planning.

AVM providers require large amounts of reliable, detailed descriptive data about properties and market transaction prices to model accurately – and this is where the qualitative data obtained through physical property inspection can help algorithms be more sensitive to risks we are still discovering.

There is still strong investor appetite for exposure to UK residential property – after all, terms that have averaged 25 years for the best part of half a century are now extending to 30, 35 and even 40 years. Match-funding the liabilities held by insurers faced with far higher longevity looks well suited to the asset class. Physical valuations remain incredibly useful and desirable for wholesale-funded lenders where ratings agencies or investors want the security of a physical inspection with the asset.

Data points are becoming the basis of every investment decision. Whether ultimately a human judgement or machine output, the source of those data points is key.